1. Field of the Invention
This invention relates to intelligent decision systems, including humanoid, social, and natural-languaging machines. More particularly, it relates to computer systems including autonomous decision systems which include means for determining relevancy, i.e., the threats to and opportunities of the autonomous decision system, present and predicted. Even more particularly, it relates to such intelligent and humanoid autonomous decision systems constructed and arranged to interact comfortably with humans, including the use of social bonding and natural languages.
The microfiche filed in the parent application shows the source code for a preferred embodiment of the present invention in the form of an entertainment or xe2x80x9cgamexe2x80x9d entitled xe2x80x9cStoryPalxe2x80x9d (TM).
2. Background and Description of the Prior Art
In the past, it has been a difficult and sought-after goal to provide general-purpose autonomous decision systems (herein also called xe2x80x9cADS""sxe2x80x9d) which can efficiently determine threats and opportunities, i.e., relevancies. In addition, there have been further goals to make such autonomous decision systems seem more xe2x80x9chumanoidxe2x80x9d in the sense of abilities to perform some human-like functions like thinking, feeling, languaging, determining relevancy, etc. Further, in order to provide comfortable interaction between such ADS""s and humans, especially in natural language transactions, requires at least that the way the ADS xe2x80x9cmakes sensexe2x80x9d of what is going on itself xe2x80x9cmakes sensexe2x80x9d to humans.
Several chief areas in which the systems used by the ADS must xe2x80x9cmake sensexe2x80x9d to most humans are: (1) the system for categorization used by the ADS to break up the infinite variety of the world and construct a finite representation of it; (2) the system for making decisions used by the ADS, e.g., by testing alternative actions and comparing the resulting alternative consequences (i.e., using a xe2x80x9cwhat-ifxe2x80x9d system); (3) the system for determining the xe2x80x9crelevancyxe2x80x9d or xe2x80x9cmeaningxe2x80x9d to (i.e., threats to and opportunities of) the ADS of various circumstances or situations; and (4) other ADS systems for accommodating such functions as determining similarity, doing learning, implementing bonding and sociality, and handling memory/history. Perhaps the major advantage which such an ADS might have is the use (sending and receiving) of natural language in interactions with humans.
In the prior art, there have been many efforts over many decades to provide such an autonomous decision system, or to at least find a good starting place for such efforts. Many xe2x80x9cfieldsxe2x80x9d have attempted this, among them Artificial Intelligence, Cognitive Science, Artificial Life, and Robotics. But the goal has been elusive and there have been few serious proposals for a good starting place, even from major approaches like logic programming, xe2x80x9cneural netsxe2x80x9d, expert systems, and xe2x80x9cfuzzy logicxe2x80x9d.
As another example, philosophers of Artificial Intelligence are still today searching to agree upon good definitions of such common mammalian/human autonomy traits as xe2x80x9cawarenessxe2x80x9d. And the scientific literature is void even of good proposals for general humanoid or machine systems of internal representation, or for general-purpose object categorization, as with primitives permitting xe2x80x9cwhether concrete is included in abstractxe2x80x9d computation, or for bonding and sociality implementation.
A primary object of the present invention is the provision of a computer system providing an improved intelligent decision system, including such systems which implement sociality and bonding, learning, and natural languaging. Another primary object of this invention is to provide an efficient autonomous decision computer system which is xe2x80x9cawarexe2x80x9d of the implications and relevancies of its circumstances, i.e., is xe2x80x9cawarexe2x80x9d of threats to it and of its opportunities, actual or impending. A further object is to provide an improved system for machine use of natural language. Yet a further object is to provide in an autonomous decision system a highly efficient system of internal representation, including a categorization system permitting efficient and computable relationships between abstracts and concretes; and further to provide such a system of internal representation having relationships which assist in providing efficiency in many areas and assists in providing natural-language abilities to an ADS. Even another object is to provide separate improved systems involving subsystem inventions of the ADS of the present invention (e.g., a virtual reality engine) for use in other fields. Other objects of this invention will become apparent with reference to the following invention descriptions.
The present invention provides, in accordance with a preferred embodiment thereof, a computer system for implementing decisions of an autonomous decision system in an environmental situation, comprising: computer processing means for processing data; storage means for storing data on a storage medium; input means for providing temporally-incremental input data about a series of such environmental situations; concrete-situation means for processing data regarding such temporally-incremental input data about such series of such environmental situations to provide a temporally-incremental series, respectively, of xe2x80x9cpresentxe2x80x9d concrete self-situation representations of such respective environmental situations, wherein each such self-situation representation comprises a self representation and a set of event representations, each such event representation being represented specifically spacio-temporally relative to such self representation, and each such event representation including a behavioral-type designation selected from a set of behavioral-type designations, each such behavioral-type designation of such set of behavioral-type designations being associated with a set of incremental behavioral self-tendencies for determining incrementally-predicted self-situation representations from a such presented self-situation representation; and a set of current-behavior designations associated with each such event representation specifying the current behaviors of each such event representation.
Further, this invention provides such a computer system wherein such representation means comprises data means for representing a particular object as part of a collection of object representations, each such object representation of such collection comprising a such behavioral-type designation, and such representation means further comprising: assignment means for processing and storing data regarding assigning characteristics to each such object representation of such collection, wherein essentially each of such characteristics comprises a subset of a set of self-tendencies and a corresponding subset of a set of self-tendency markers, such set of self-tendency markers having a 1-to-1 correspondence with such set of self-tendencies, one unique marker from such set of self-tendency markers corresponding respectively with each self-tendency of such set of self-tendencies, such subset of self-tendencies being constructed and arranged to permit a determination of the expected behavior of each such object representation with respect to any mappable representation of other object representations from such collection of object representations, each such self-tendency consisting essentially of an instruction for self-behavior (of any first object representation to which such self-tendency may be assigned) on the condition that any mappable representation of object representations from such collection, including such first object representation, from the viewpoint of such first object representation, is included in a specified self-relation selected from a set of self-relations, where each self-relation of such set of self-relations comprises a specified space-time relation among a such first object representation and at least one such other object representation, each such other object representation being specified as a subset of a set of self-tendency markers, each such subset of self-tendency markers corresponding to the subset of self-tendencies assigned to each such other object representation.
Even further, this invention provides such a computer system wherein: each such self-tendency marker has a first marker part selected from a set of first marker parts and a second marker part selected from a set of second marker parts, such set of first marker parts having a 1-to-1 correspondence with such set of self-relations, and such set of second marker parts having a 1-to-1 correspondence with such set of instructions for self-behavior. And it provides such a computer system further comprising: prediction means for processing data regarding such xe2x80x9cpresentxe2x80x9d concrete self-situation representations of such respective environmental situations to determine the representations of a set of incrementally-predicted self-situations, predicted as incremental consequences from such presented self-situation representation; and relevancy means for processing relevancy data to determine the self-relevancy of a such presented self-situation representation; and the self-relevancy of such set of incrementally-predicted self-situation representations; whereby threats to and opportunities of such autonomous self decision system may be determined. It also provides such a computer system wherein such prediction means comprises: means for processing data for incremental computation, considering each such set of incremental behavioral self-tendencies associated with a such behavioral-type designation of each such event representation, of the expected incremental changes in each such event representation of each such presented self-situation representation and of each such incrementally-predicted self-situation representation for a selected number, I, of increments, thereby producing, by such incremental computation, a series of I incrementally-predicted self-situation representations from such presented self-situation representation.
In addition, this invention provides such a computer system wherein such relevancy means comprises: means for storing data for hierarchical planning comprising a hierarchical set of n problem representations; and m plan-sets of hierarchical subgoal representations, each such plan-set of hierarchical subgoal representations being associated with at least one of such set of n problem representations. And it provides such a computer system wherein such problem representations and such subgoal representations of such relevancy means comprise expression types from the class consisting of relational-geometric expressions and relational-quantity expressions; and, further, wherein such relevancy means comprises: first situation-inclusional means for processing data for comparing such presented self-situation representation and such set of incrementally-predicted self-situation representations with such problem representations and such subgoal representations, including problem means for processing data for determining which of such hierarchical set of n problems includes a particular such self-situation representation, plan means for processing data for determining which of such hierarchical subgoal representations includes a particular such self-situation representation, and predictive planning means for processing data for determining incrementally which incrementally-predicted self-situation representations are included in which problem representations and which subgoal representations. And it also provides such a computer system wherein: each such incremental self tendency comprises an instruction for incremental self-behavior (of any first such event representation to which such incremental self-tendency may be assigned) on the condition that any such self situation representation including such first event representation, from the viewpoint of such first event representation, is included in a specified self-relation; and such prediction means comprises second situation-inclusional means for processing data for comparing such self-situation representation including such first event representation, from the viewpoint of such first event representation, and such specified self relation of such each incremental self tendency.
It also provides such a computer system wherein: such first situation-inclusional means (of such relevancy means) consists essentially of first computational means; such second situation-inclusional means (of such prediction means) consists essentially of second computational means; and such first computational means comprises such second computational means; and, further, wherein such first computational means and such second computational means comprise a single parallel processing system. And it provides such a computer system further comprising: feeling means for processing data for providing to such self representation information about self-emotions and self-metabolism; and recognition means for processing data regarding sensor status and a list of object representations each with an associated normal sensor identification and an associated of behavioral-type designations, to provide a recognized object representation; wherein such recognition means comprises association means for processing data regarding associating with a such object representation an identified first set of recognition factors selected from a second set of recognition factors; wherein each such recognition factor consists essentially of a marker-reference to a specified range or specified reading of an input means representation; and wherein a set of such behavioral-type designations assigned to such object representation depends upon such identified first set of recognition factors associated with such object representation.
Moreover, this invention provides a computer system further comprising what-iffing means for processing data for selecting and specifying a self trial decision to such presented self representation for use in determining such set of predicted self-situation representations. And it provides such a computer system wherein: such relevancy data comprises a set of hierarchically-organized relevance self-relations, where essentially each relevance self-relation of such set of relevance self-relations comprises a specified space-time relation among a such self representation and at least one such other object representation, each such other object representation being specified as a subset of such set of self-tendency markers, each such subset of self-tendency markers corresponding to the such subset of self-tendencies assignable to each such other object representation; and such computer system further comprises a first situation-inclusional means for processing data regarding determining which of such relevance self-relations include any such self situation representations. And it provides such a computer system wherein such prediction means comprises: simulation means for processing data for simulating through time from a beginning structured-situation of the circumstances of any objects of such collection which are in any mapping representation, such simulation means including means for processing data for selecting, from each such subset of self-tendencies so constructed and arranged to permit a determination of the expected behavior of each such object with respect to any mappable representation of other objects from such collection, the beginning incremental behavioral tendency of each object of such beginning structured-situation of the given beginning mapping representation of objects; means for processing data for performing, with respect to such beginning structured-situation, such beginning incremental behavioral tendency of each such object, to transform such beginning structured-situation to a first amended structured-situation; means for processing data for selecting, for each such object of such first amended structured-situation, the next incremental behavioral tendency of each such object; means for processing data for performing, with respect to such first amended structured-situation, such next incremental behavioral tendency of each such object, to transform such first amended structured-situation to a second amended structured-situation; and means for processing data for continuing to perform, for a selected period, appropriate succeeding incremental behavioral tendencies of each such object to continue to transform each succeeding amended structured situation to a next succeeding structured-situation. It also provides such a computer system wherein such second situational inclusional means comprises a set of parallel computing structures, each one of such parallel computing structures being constructed and arranged to determine the inclusion within a specified such relational self-situation of any presented such structured self-situation.
According to a preferred embodiment thereof, this invention also provides a computer system for providing emotional expression in an autonomous decision system, comprising: computer processing means for processing data; storage means for storing data on a storage medium; planning-data means for storing data for providing plan capability to such autonomous decision system; planning means for processing data regarding circumstances of such autonomous decision system to provide planning selections and planning status; status means for processing data regarding current planning status to provide emotion-source data; and emotion means for processing data regarding emotion-source information to provide current emotion status. It further provides such a computer system further comprising expression means for processing data regarding current emotion status to provide body-expression data. And it provides such a computer system further comprising: sensor means for providing sensor data for the autonomous decision system; and effector means for processing data regarding body expression to provide output signals for effectors; and, further, wherein: such autonomous decision system is humanoid; such expression means for processing data regarding current emotion status to provide body-expression data comprises a provider of facial-expression data including data regarding smiles and frowns; and, further, wherein such emotion means for processing data regarding emotion source information to provide current emotion status comprises a provider of current status of not-copying arousal of such humanoid autonomous decision system, including data regarding self not-copying and other not-copying; and, further, wherein such status means for processing data regarding current planning status to provide emotion-source data comprises a provider of data regarding fear, hopelessness, and disappointment; and, further, wherein such status means for processing data regarding current planning status to provide emotion-source data further comprises a provider of data regarding frustration, surprise, and muscle relief.
Even moreover, this invention provides such a computer system further comprising: social data means for processing data regarding a non-self life form for assigning to such non-self life form a kind-number representing a relative similarity of such non-self life form to the self""s own kind; social processing means for processing data for making a similarity comparison of a decision of a such non-self life form when in a first situation to a decision of the self if the self were in such first situation and evaluating such comparison for degree of decision similarity and adjusting such kind-number to reflect such decision similarity of such non-self life form. It also provides such a computer system further comprising: planning means for providing plan capability to such autonomous decision system, wherein such planning means comprises a set of hierarchically-organized abstract self-problem representations, and in association with essentially each of such abstract self-problem representations, a set of hierarchically-organized abstract self-plan representations each comprising a set of abstract self-subgoal representations, wherein at least one such abstract self-problem representation is the problem of the self not-copying with a such non-self life form; wherein such status means for processing data regarding current planning status to provide emotion-source data comprises a provider of data regarding fear, hopelessness, and disappointment, comprising incremental representations of xe2x80x9cfearxe2x80x9d in amounts essentially hierarchically ordered according to such hierarchical set of self-problem representations, and incremental representations of xe2x80x9chopelessnessxe2x80x9d depending essentially upon whether, in the operation of such planning means, in the self-plan representation for the highest active hierarchical self-problem representation, none of the subgoal representations is active; and wherein an emotion amount associated with such problem of the self not-copying with such non-self life form is structured and arranged to be essentially proportional to such kind-number associated with such non-self life form.
Also, in accordance with a preferred embodiment hereof, this invention provides a computer system for implementing natural language functions in a humanoid autonomous decision system, comprising: computer processing means for processing data; storage means for storing data on a storage medium wherein such data comprises non-linguistic discrete data-types and, conforming to each of such discrete non-linguistic data-types, a set of non-linguistic discrete data elements; input means for providing information about current circumstances of the humanoid autonomous decision system; output means for implementing decisions of the humanoid autonomous decision system; relevance means for providing information regarding the relevance to the humanoid autonomous decision system of such current circumstances, comprising self-representation means for processing data regarding xe2x80x9cselfxe2x80x9d to provide at least one xe2x80x9cselfxe2x80x9d representation, structured-situation means for processing data regarding such current circumstances to provide a first non-linguistic structured xe2x80x9cselfxe2x80x9d-situation representation, relational-situation storage means for providing data regarding a set of hierarchically-organized, relevant, non-linguistic relational xe2x80x9cselfxe2x80x9d-situations, and inclusional means for processing data to determine inclusions of a such first non-linguistic structured xe2x80x9cselfxe2x80x9d-situation within such non-linguistic relational xe2x80x9cselfxe2x80x9d-situations to determine any relevance of such first structured xe2x80x9cselfxe2x80x9d-situation to a such xe2x80x9cselfxe2x80x9d of such relevance means, wherein such data regarding such set of hierarchically-organized, relevant, non-linguistic relational xe2x80x9cselfxe2x80x9d-situations includes data regarding a set of hierarchically-organized problem relational xe2x80x9cselfxe2x80x9d-situations, and in association with essentially each of such problem relational xe2x80x9cselfxe2x80x9d-situations, a set of hierarchically-organized plan relational xe2x80x9cselfxe2x80x9d-situations; type-linking storage means for providing data regarding respectively linking essentially each such discrete data-type of such humanoid autonomous decision system with a respective word/phrase category of a first natural language, and respectively linking selected words/phrases of each such linked word/phrase category of such first natural language with respective such discrete data elements of each such discrete data-type so linked with a such linked word/phrase category; and data transformation means for processing data regarding a first communication to be made by such humanoid autonomous decision system to transform a specified set of non-linguistic data elements into a such first communication in such first natural language, comprising identification means for processing data regarding identifying which of such discrete data elements of such discrete data-types is to form part of such first communication, snippet means for processing data regarding selecting natural-language snippets for pointing to the such categories of such natural-language corresponding to whichever of such discrete data-types includes each such discrete data element which is to form part of such first communication, vocabulary means for processing data regarding selecting a word/phrase of such natural-language corresponding to each such discrete data element which is to form part of such first communication, and grammar means for processing data regarding producing from the grammar practices of such natural language and from such snippet selections and from such word/phrase selections such first communication in such natural language.
Additionally, it provides such a computer system further comprising: what-if means comprising trial-decision means for providing data regarding, in association with each of such relevance self-relations, a set of hierarchically-organized xe2x80x9cselfxe2x80x9d trial decisions; selecting means for processing data regarding such xe2x80x9cselfxe2x80x9d trial decisions to provide data regarding, when a such relevance self-relation has included a such specific circumstance, a current selected such xe2x80x9cselfxe2x80x9d trial decision; trial-decision-testing means for processing data regarding using such relevance means to determine the relevance of selected amended structured-situations arising by simulation from using a selected such xe2x80x9cselfxe2x80x9d trial decision for the xe2x80x9cselfxe2x80x9d object within the then such specific circumstance; and self-decision-selecting means for processing data regarding selecting, depending upon the then specific relevances upon operation of such trial-decision-testing means, a such xe2x80x9cselfxe2x80x9d trial decision as a then self-decision of such intelligent system. And it provides such a computer system further comprising: sequential story data means for acquiring, when such first communication is to be the telling of a xe2x80x9ctruexe2x80x9d and xe2x80x9cinterestingxe2x80x9d xe2x80x9cpersonal historyxe2x80x9d story about the experiences of such humanoid autonomous decision system, sequential data for use in such telling, comprising: for use in a first story element of such story, first means for processing data, when a first selected level of a self-pain signal has been attained by such humanoid autonomous decision system, regarding first data about a current time and a current place and a xe2x80x9cconcretizedxe2x80x9d current problem relational xe2x80x9cselfxe2x80x9d-situation to provide data regarding the concrete objects of a then current structured xe2x80x9cselfxe2x80x9d-situation which are included in such current problem relational xe2x80x9cselfxe2x80x9d-situation; for use in a second story element of a such story, second means for processing data, when a such then current structured xe2x80x9cselfxe2x80x9d-situation is included in a first plan relational xe2x80x9cselfxe2x80x9d-situation, regarding second data about a current strategy and a xe2x80x9cconcretizedxe2x80x9d current such plan relational xe2x80x9cselfxe2x80x9d-situation, to provide data regarding the concrete objects of a such then current structured xe2x80x9cselfxe2x80x9d-situation which are included in such first plan relational xe2x80x9cselfxe2x80x9d-situation; for use in a third story element of a such story, third means for processing data, when a such then current structured xe2x80x9cselfxe2x80x9d-situation is included in a second plan relational xe2x80x9cselfxe2x80x9d-situation, regarding third data about a current strategy and a xe2x80x9cconcretizedxe2x80x9d such second plan relational xe2x80x9cselfxe2x80x9d-situation, to provide data regarding the concrete objects of a such then current structured xe2x80x9cselfxe2x80x9d-situation which are included in such second plan relational xe2x80x9cselfxe2x80x9d-situation; for use in a sequential story element of a such story, fourth means for processing data, when a such sequential current structured xe2x80x9cselfxe2x80x9d-situation is included in a next identified plan relational xe2x80x9cselfxe2x80x9d-situation, regarding sequential data about a then current strategy and a xe2x80x9cconcretizedxe2x80x9d such next identified plan relational xe2x80x9cselfxe2x80x9d-situation, to provide data regarding the concrete objects of a such sequential current structured xe2x80x9cselfxe2x80x9d-situation which are included in such next identified plan relational xe2x80x9cselfxe2x80x9d-situation; and for use in a final story element of a such story, fifth means for processing data, when a second selected level of a self-pleasure signal has been attained by such humanoid autonomous decision system, regarding final data about a xe2x80x9cconcretizedxe2x80x9d such identified goal plan relational xe2x80x9cselfxe2x80x9d-situation, to provide data regarding the concrete objects of a such final current structured xe2x80x9cselfxe2x80x9d-situation which are included in such identified goal plan relational xe2x80x9cselfxe2x80x9d-situation. Even additionally, this invention provides such a computer system further comprising: means for storing data regarding such sequential data for use in such telling of a such story; means for processing data regarding searching of any such stored sequential data to provide user-controlled selection among such stored sequential data; and means for processing data regarding a user-selected later use of such sequential data to provide a later telling of a story based upon such stored sequential data.
Yet further, according to a preferred embodiment thereof, the present invention provides a computer system for implementing first natural language interpretation functions in a humanoid autonomous decision system interpreting incoming first natural language from an other, comprising: computer processing means for processing data; storage means for storing data on a storage medium wherein such data comprises non-linguistic discrete data-types and, conforming to each of such discrete non-linguistic data-types, a set of non-linguistic discrete data elements; type-linking storage means for providing data regarding respectively linking essentially each such discrete data-type of such humanoid autonomous decision system with a respective word/phrase category of such first natural language, and respectively linking selected words/phrases of each such linked word/phrase category of such first natural language with respective such discrete data elements of each such discrete data-type so linked with a such linked word/phrase category; input means for providing input information about characteristics of such incoming natural language sufficient to identify each vocabulary element, snippet type for each such element, and grammatical function for each such element; translation means for processing data regarding such input information to provide a non-natural-language concrete circumstance interpretation of such input information; relevance means for providing information regarding the relevance to the humanoid autonomous decision system of such circumstance interpretation, comprising relational-situation storage means for providing data regarding a set of hierarchically-organized, relevant, non-linguistic relational xe2x80x9cselfxe2x80x9d-situations, and inclusional means for processing data to determine inclusions of such non-natural-language concrete circumstance interpretation within such non-linguistic relational xe2x80x9cselfxe2x80x9d-situations to determine any relevance of such non-natural-language concrete circumstance interpretation a such xe2x80x9cselfxe2x80x9d of such relevance means, wherein such data regarding such set of hierarchically-organized, relevant, non-linguistic relational xe2x80x9cselfxe2x80x9d-situations includes data regarding a set of hierarchically-organized problem relational xe2x80x9cselfxe2x80x9d-situations, and in association with essentially each of such problem relational xe2x80x9cselfxe2x80x9d-situations, a set of hierarchically, organized plan relational xe2x80x9cselfxe2x80x9d-situations.
Yet additionally, it provides such a computer system wherein such interpreting humanoid autonomous decision system has abilities to select for use in interpretation similar cognitive, relevancy, and emotion systems to those of the other; and, further, wherein such translation means comprises natural-language default-selecting means for processing data regarding selection of non-natural-language data types and data for correspondence with such incoming information. And it provides such a computer system further comprising: story-interpretation means for processing data regarding a story-series of such incoming informations to provide a story-series of such non-natural-language concrete circumstance interpretations; and learning means for processing data regarding such story-series of such non-natural-language concrete circumstance interpretations to provide a learned modification of a such non-linguistic discrete data element, wherein such story-series of such non-natural-language concrete circumstance interpretations is treated as a temporally-incremental series, respectively, of xe2x80x9cpresentxe2x80x9d concrete self-situation representations of a temporally-incremental series of respective environmental situations.
Yet moreover, it provides such a computer system wherein: each story element of such story-series of such non-natural-language concrete circumstance interpretations comprises a self representation and a set of event representations, each such event representation being represented specifically spacio-temporally relative to such self representation, and each such event representation including a behavioral-type designation selected from a set of behavioral-type designations, each such behavioral-type designation of such set of behavioral-type designations being associated with a set of incremental behavioral self-tendencies for determining incrementally-predicted self-situation representations from a such presented self-situation representation; and a set of current-behavior designations associated with each such event representation specifying the current behaviors of each such event representation. Also, it provides such a computer system wherein essentially each such event representation comprises an object representation representing a particular object as part of a collection of such object representations, each such object representation of such collection comprising a such behavioral-type designation comprising characteristics of each such object representation of such collection, wherein essentially each of such characteristics comprises a subset of a set of self-tendencies and a corresponding subset of a set of self-tendency markers, such set of self-tendency markers having a 1-to-1 correspondence with such set of self-tendencies, one unique marker from such set of self-tendency markers corresponding respectively with each self-tendency of such set of self-tendencies, such subset of self-tendencies being constructed and arranged to permit a determination of the expected behavior of each such object representation with respect to any mappable representation of other object representations from such collection of object representations, each such self-tendency consisting essentially of an instruction for self-behavior (of any first object representation to which such self-tendency may be assigned) on the condition that any mappable representation of object representations from such collection, including such first object representation, from the viewpoint of such first object representation, is included in a specified self-relation selected from a set of self-relations, where each self-relation of such set of self-relations comprises a specified space-time relation among a such first object representation and at least one such other object representation, each such other object representation being specified as a subset of a set of self-tendency markers, each such subset of self-tendency markers corresponding to the subset of self-tendencies assigned to each such other object representation.
Also, this invention provides such a computer system wherein: such data regarding a set of hierarchically-organized, relevant, non-linguistic relational xe2x80x9cselfxe2x80x9d-situations comprises a set of hierarchically-organized abstract self-problem representations, and in association with essentially each of such abstract self-problem representations, a set of hierarchically-organized abstract self-plan representations each comprising a set of abstract self-subgoal representations. And it provides such a computer system further comprising: means for processing data regarding such self-problem representations and such self-plan representations to provide xe2x80x9cself-painxe2x80x9d and xe2x80x9cself-pleasurexe2x80x9d representations having assessable quantities; means for processing data regarding such story elements of such story-series of such non-natural-language concrete circumstance interpretations to identify a first series of such story elements which result in a selected level of unpredicted xe2x80x9cself-painxe2x80x9d; and means for processing data regarding such first series of such story elements to create a learned self-problem representation. It further provides such a computer system further comprising: means for processing data regarding such story elements of such story-series of such non-natural-language concrete circumstance interpretations to identify a second series of such story elements which result in a selected level of unpredicted xe2x80x9cself-pleasurexe2x80x9d; and means for processing data regarding such second series of such story elements to create a learned self-subgoal representation.
Also, in accordance with a preferred embodiment thereof, this invention provides a computer system for machine learning from an environmental situation in an autonomous decision system, comprising: computer processing means for processing data; storage means for storing data on a storage medium; input means for providing temporally-incremental input data about a series of such environmental situations; concrete-situation means for processing data regarding such temporally-incremental input data about such series of such environmental situations to provide a temporally-incremental series, respectively, of xe2x80x9cpresentxe2x80x9d concrete self-situation representations of such respective environmental situations, wherein each such self-situation representation comprises a self representation and a set of event representations, each such event representation being represented specifically spacio-temporally relative to such self representation, and each such event representation including a behavioral-type designation selected from a set of behavioral-type designations, each such behavioral-type designation of such set of behavioral-type designations being associated with a set of incremental behavioral self-tendencies for determining incrementally-predicted self-situation representations from a such presented self-situation representation; and a set of current-behavior designations associated with each such event representation specifying the current behaviors of each such event representation.
And this invention also provides such a computer system further comprising: predicted-situation means for processing data regarding a first of a such series of xe2x80x9cpresentxe2x80x9d concrete self-situation representations of such respective environmental situations to provide an incremental simulation of a set of xe2x80x9cpredictedxe2x80x9d concrete self-situation representations; comparing means for processing data regarding, for a corresponding particular time, a such xe2x80x9cpredictedxe2x80x9d concrete self-situation representation with a such corresponding xe2x80x9cpresentxe2x80x9d concrete self-situation representation to identify any selected minimum event differences between such compared concrete representations; difference-storing means for storing data regarding such concrete self-situation representations having at least such identified minimum event difference and such particular xe2x80x9cpresentxe2x80x9d concrete self-situation representation from which such identified xe2x80x9cpredictedxe2x80x9d concrete self-situation representation was computed; choosing means for processing data regarding choosing a modification in a such incremental behavioral self-tendency likely to decrease such event difference between such compared representations; testing means for processing data regarding, for such corresponding particular time, a such xe2x80x9cpredictedxe2x80x9d concrete self-situation representation and a such corresponding xe2x80x9cpresentxe2x80x9d concrete self-situation representation to provide a new identified xe2x80x9cpredictedxe2x80x9d concrete self-situation representation using such modification chosen for such incremental behavioral self-tendency; new-prediction means for processing data regarding comparing such new identified xe2x80x9cpredictedxe2x80x9d concrete self-situation representation with such corresponding former xe2x80x9cpredictedxe2x80x9d concrete self-situation representation to identify any remaining such event differences; and heuristic means for processing data regarding such modification and such event differences to heuristically choose further processing of data among at least the following: test a further modification of a such incremental behavioral self-tendency, or select for storage a modified incremental behavioral tendency, or combine for storage a such modified incremental behavioral tendency with a corresponding original incremental behavioral tendency as a replacement incremental behavioral tendency.
Further, this invention provides such a computer system wherein; each representation of such temporally-incremental series, respectively, of xe2x80x9cpresentxe2x80x9d concrete self-situation representations of such respective environmental situations comprises a self representation and a set of event representations, each such event representation being represented specifically spacio-temporally relative to such self representation, and each such event representation including a behavioral-type designation selected from a set of behavioral-type designations, each such behavioral-type designation of such set of behavioral-type designations being associated with a set of incremental behavioral self-tendencies for determining incrementally-predicted self-situation representations from a such presented self-situation representation; and a set of current-behavior designations associated with each such event representation specifying the current behaviors of each such event representation. And it provides such a computer system wherein essentially each such event representation comprises an object representation representing a particular object as part of a collection of such object representations, each such object representation of such collection comprising a such behavioral-type designation comprising characteristics of each such object representation of such collection, wherein essentially each of such characteristics comprises a subset of a set of self-tendencies and a corresponding subset of a set of self-tendency markers, such set of self-tendency markers having a 1-to-1 correspondence with such set of self-tendencies, one unique marker from such set of self-tendency markers corresponding respectively with each self-tendency of such set of self-tendencies, such subset of self-tendencies being constructed and arranged to permit a determination of the expected behavior of each such object representation with respect to any mappable representation of other object representations from such collection of object representations, each such self-tendency consisting essentially of an instruction for self-behavior (of any first object representation to which such self-tendency may be assigned) on the condition that any mappable representation of object representations from such collection, including such first object representation, from the viewpoint of such first object representation, is included in a specified self-relation selected from a set of self-relations, and where each self-relation of such set of self-relations comprises a specified space-time relation among a such first object representation and at least one such other object representation, each such other object representation being specified as a subset of a set of self-tendency markers, each such subset of self-tendency markers corresponding to the subset of self-tendencies assigned to each such other object representation.
Yet in addition, it provides such a computer system further comprising: means for storing representation data regarding a set of hierarchically-organized, relevant, non-linguistic relational xe2x80x9cselfxe2x80x9d-situations comprising a set of hierarchically-organized abstract self-problem representations, and in association with essentially each of such abstract self-problem representations, a set of hierarchically-organized abstract self-plan representations each comprising a set of abstract self-subgoal representations; and, also, further comprising: means for processing data regarding such self-problem representations and such self-plan representations to provide xe2x80x9cself-painxe2x80x9d and xe2x80x9cself-pleasurexe2x80x9d representations having assessable quantities; means for processing data regarding representation elements of such temporally-incremental series, respectively, of xe2x80x9cpresentxe2x80x9d concrete self-situation representations of such respective environmental situations to identify a first series of such representation elements which result in a selected level of unpredicted xe2x80x9cself-painxe2x80x9d; and means for processing data regarding such first series of such representation elements to create a learned self-problem representation; and, also, further comprising: means-for processing data regarding such representation elements of such temporally-incremental series, respectively, of xe2x80x9cpresentxe2x80x9d concrete self-situation representations of such respective environmental situations to identify a second series of such representation elements which result in a selected level of unpredicted xe2x80x9cself-pleasurexe2x80x9d; and means for processing data regarding such second series of such representation elements to create a learned self-subgoal representation.
Yet moreover, according to a preferred embodiment thereof, this invention provides a computer system for an entertainment system, comprising: computer simulation means for processing data regarding a user-selected xe2x80x9cworldxe2x80x9d-representation containing user-selected spacio-temporally located xe2x80x9cobjectxe2x80x9d-representations to provide incremental simulation-stepping of such xe2x80x9cworldxe2x80x9d-representation; computer is interface means for processing data for providing a natural-language interface for user selection of non-natural-language characteristics of a such xe2x80x9cobjectxe2x80x9d-representation; computer interface means for processing data for providing an interface for user placement of a such xe2x80x9cobjectxe2x80x9d-representation into such xe2x80x9cworldxe2x80x9d-representation; computer interface means for processing data for providing an interface for placement into such xe2x80x9cworldxe2x80x9d-representation, as a such xe2x80x9cobjectxe2x80x9d-representation, of an autonomous decision system; wherein such autonomous decision system comprises representation means for processing data essentially from such xe2x80x9cworldxe2x80x9d-representation for presenting a selected self-situation (for such autonomous decision system) representation, such presented self-situation representation comprising a self representation and a set of event representations, each such event representation being represented specifically spacio-temporally relative to such self representation, and prediction means for processing data for determining the representations of a set of incrementally-predicted self-situations, predicted as incremental consequences from such presented self-situation representation; wherein such prediction means comprises such simulation means.
It also provides such a computer system wherein such autonomous decision system further comprises: relevancy means for processing data for determining the self-relevancy of a such presented self-situation representation; and determining the self-relevancy of such set of incrementally-predicted self-situation representations; whereby threats to and opportunities of such autonomous self decision system may be determined. And it also provides such a computer system wherein such autonomous decision system further comprises: feeling means for processing data regarding such incremental self-relevancies to determine the relative values of a set of selected simulated-xe2x80x9cemotionsxe2x80x9d; and look-for means for processing data regarding planning status of such autonomous decision system to provide assistance to a sensor system regarding what to look for. And it further provides such a computer system further comprising: display means for displaying a created face of such autonomous decision system; and facial-expression means for processing data regarding such feeling means to determine appropriate facial-expression instructions for creating such face; and, further, wherein such display means comprises lip-synch means for processing data for simulating mouth movement of such face in simulated correspondence to human natural languaging.
Yet even further, it provides such a computer system wherein such autonomous decision system further comprises: storage means for data wherein such data comprises non-linguistic discrete data-types and, conforming to each of such discrete non-linguistic data-types, a set of non-linguistic discrete data elements; type-linking storage means for providing data regarding respectively linking essentially each such discrete data-type of such humanoid autonomous decision system with a respective word/phrase category of a first natural language, and respectively linking selected words/phrases of each such linked word/phrase category of such first natural language with respective such discrete data elements of each such discrete data-type so linked with a such linked word/phrase category; and data transformation means for processing data regarding a first communication to be made by such humanoid autonomous decision system to transform a specified set of non-linguistic data elements into a such first communication in such first natural language, comprising identification means for processing data regarding identifying which of such discrete data elements of such discrete data-types is to form part of such first communication, snippet means for processing data regarding selecting natural-language snippets for pointing to the such categories of such natural-language corresponding to whichever of such discrete data-types includes each such discrete data element which is to form part of such first communication, vocabulary means for processing data regarding selecting a word/phrase of such natural-language corresponding to each such discrete data element which is to form part of such first communication, and grammar means for processing data regarding producing from the grammar practices of such natural language and from such snippet selections and from such word/phrase selections such first communication in such natural language; and, further, wherein such first communication is simulated to originate in such face of such autonomous decision system.
And it also provides such a computer system further comprising: metabolism means for processing data for determining the values of a set of simulated-xe2x80x9cmetabolismxe2x80x9d quantities for a such xe2x80x9cobjectxe2x80x9d-representation; and display means for selectively displaying such values of such set of simulated-xe2x80x9cmetabolismxe2x80x9d quantities for a such xe2x80x9cobjectxe2x80x9d-representation; wherein such simulation means comprises such metabolism means. It also provides such a computer system further comprising: animation means for processing data for selecting and displaying a viewable animation of such xe2x80x9cobjectxe2x80x9d-representation; wherein such simulation means comprises a set of current-behavior designations associated with each such xe2x80x9cobjectxe2x80x9d-representation of a such xe2x80x9cworldxe2x80x9d-representation specifying the current behaviors of each such xe2x80x9cobjectxe2x80x9d-representation; and wherein such animation means uses such set of current-behavior designations associated with each such xe2x80x9cobjectxe2x80x9d-representation of a such xe2x80x9cworldxe2x80x9d-representation in such selecting of a such viewable animation of such xe2x80x9cobjectxe2x80x9d-representation; and, further, wherein such relevancy means comprises such non-linguistic discrete data elements and such data transformation means comprises story-telling means for processing data regarding data elements from such relevancy means for instructing story-telling elements to provide story-telling by such autonomous decision system. And it also provides such a computer system further comprising story-saving means for processing data to provide saving and later re-telling of stories created by such story-telling means; and, also, further comprising: interface means for providing an interface and for processing data for user-asking of questions of such autonomous decision system.
Yet additionally, in accordance with a preferred embodiment thereof, this invention provides a computer program for computationally-efficient representation for classifying natural objects along a concrete-to-abstract scale in such manner as to support improved correspondence with natural languages, comprising, in combination, the steps of: storing in a computer information-storage device a set of non-natural-language markers, each such marker being unique; associating a subset of such set with a representation of a such natural object; and identifying a more-abstract representation of such natural object by a sub-subset of such subset. And it provides a computer program wherein such more-abstract representation of such natural object is identified by one of such non-natural-language markers. It also provides a computer program comprising the steps of: storing in such computer information-storage device a set of non-natural-language behavioral self-tendencies, each such self-tendency being unique; and associating each such unique marker of such set of markers, 1-to-1, with a corresponding such unique self-tendency; wherein each such self-tendency comprises a form attachable to any such natural object for predictive purposes; and, further, wherein essentially each such self-tendency comprises a spacio-temporal relationship between a self representation and at least one other representation of a such natural-object; and, further, wherein such at least one other representation of a such natural-object comprises at least one such marker.
And this invention provides such a computer program wherein a such self-tendency comprises xe2x80x9cdoingxe2x80x9d information y; about a such representation in such spacio-temporal relationship. Also, it provides such a computer program further comprising the step of: associating an identifying unique natural-language string in a first natural language to essentially each of such representations of a such natural object; wherein each such natural-language string identifies each such representation of a such natural object in such first natural language along a concrete-to-abstract scale reflecting a relative number of such markers associated with such each representation of a such natural object.
Yet in addition, according to a preferred embodiment thereof, this invention provides a computer program for making a mapping representation of xe2x80x9cconcretexe2x80x9d objects, usable in a computer simulation program, comprising the steps of: storing in computer storage representations of a set of xe2x80x9cconcretexe2x80x9d objects; associating with each such xe2x80x9cconcretexe2x80x9d-object representation an identified first set of prediction factors selected from a second set of prediction factors; wherein each such prediction factor of such second set of prediction factors consists essentially of an instruction rule for the incremental simulation-type movement of such associated xe2x80x9cconcretexe2x80x9d-object representation when in a specified spacio-temporal relationship with a set of identified xe2x80x9cabstractxe2x80x9d-object representations; and wherein each such xe2x80x9cabstractxe2x80x9d-object representation comprises a prediction-factor marker, each such prediction-factor marker having a 1-to-1 correspondence with a unique one of such second set of prediction factors. And it also provides such a computer program wherein: such identified first set of prediction factors is hierarchically organized; and such identified first set of prediction factors is sufficient for the determination of an incremental simulation-type movement of such associated xe2x80x9cconcretexe2x80x9d-object representation when such associated xe2x80x9cconcretexe2x80x9d-object representation is in any mapping representation with a set of other xe2x80x9cconcretexe2x80x9d-object representations.
Also, this invention provides such a computer program further comprising the step of: associating with such xe2x80x9cconcretexe2x80x9d-object representation an identified first set of recognition factors selected from a second set of recognition factors; wherein each of such second set of recognition factors consists essentially of a reference to a specified range or specified reading of a specified sensor device wherein such identified first set of prediction factors associated with such xe2x80x9cconcretexe2x80x9d-object representation depends upon such identified first set of recognition factors associated with such xe2x80x9cconcretexe2x80x9d-object representation; wherein such identification of each such xe2x80x9cabstractxe2x80x9d-object representation comprises a first set of prediction-factor name-markers selected from a second set of prediction-factor name-markers; and wherein such second set of prediction-factor name-markers has a 1-to-1 correspondence with such second set of prediction factors. And it further provides such a computer program further comprising the step of: associating a unique natural-language reference with such representations of each such xe2x80x9cconcretexe2x80x9d object and each such xe2x80x9cabstractxe2x80x9d object.
Further, according to a preferred embodiment thereof, this invention provides a computer program for providing emotional expression in an autonomous decision system, comprising the steps of: storing in a computer information-storage device planning data providing plan capability to such autonomous decision system; using information regarding environmental circumstances of such autonomous decision system, providing planning selections and planning status; using information about current such planning status, providing emotion-source data; using current such emotion-source data, providing current emotion status. And it provides such a computer program further comprising the steps of: making and storing in such computer information-storage device a subset of such planning data about: a first plan regarding whether the self of such autonomous decision system is then copying with a non-self creature of such environmental circumstances, and a second plan regarding whether a such non-self creature is then copying with such self; evaluating an extent of a such copying by: making a similarity comparison of a decision of a such non-self creature when in a first circumstance situation to a decision of the self if the self were in such first circumstance situation and evaluating such comparison for degree of decision similarity; including in such emotion-source data information correlated with such extent of a such copying; and including in such current emotion status a status of not-copying emotion of such autonomous decision system.
Even further, it provides such a computer program further comprising the steps of: assigning to such non-self creature and storing in such computer-information storage device a kind-number representing an extent of relative similarity of such non-self creature to such self""s own kind; and adjusting such kind-number to at least partially reflect such extent of a such copying by such non-self creature. And it provides such a computer program further comprising the step of: assigning an emotion amount, for association with such emotion-source data effecting such current emotion status of such not-copying emotion of such autonomous decision system, essentially proportional to a current such kind-number associated with such non-self creature. It also provides such a computer program wherein: such planning data comprises a set of hierarchically-organized abstract self-problem representations, and in association with essentially each of such abstract self-problem representations, a set of hierarchically-organized abstract self-plan representations each comprising a set of abstract self-subgoal representations, wherein at least one such abstract self-problem representation is the problem of the self not-copying with a such non-self creature.
Moreover, this invention provides such a computer program wherein: such emotion-source data comprises data regarding fear, hopelessness, and disappointment, comprising incremental representations of xe2x80x9cfearxe2x80x9d in amounts essentially hierarchically ordered according to such hierarchical set of self-problem representations, and incremental representations of xe2x80x9chopelessnessxe2x80x9d depending essentially upon whether, in the operation of such planning means, in the self-plan representation for the highest active hierarchical self-problem representation, none of the subgoal representations is active; and such emotion-source data comprises an emotion amount associated with such problem of the self not-copying with such non-self creature which is structured and arranged to be essentially proportional to such kind-number associated with such non-self creature. And it provides such a computer program further comprising the steps of: providing sensor means for providing sensor data for such autonomous decision system; using such current emotion status, providing data regarding body expression to provide output signals for use by effectors; wherein such data regarding body expression comprises data regarding smiles and frowns; and wherein a smile is associated with a creature feeling copied with and a frown is associated with a creature feeling not copied with. And it provides such a computer program wherein: such emotion-source data further comprises a provider of data regarding frustration, surprise, and muscle relief.